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Analysis of Covariance

2021
ANCOVA of designed experiments combines one categorical and one continuous explanatory variable. Panel plots are usually the best way to graphically display ANCOVA designs, with a separate linear regression within each level of the factor. ANCOVA can test for effects of both variables and interactions between them.
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Analysis of Variance and Covariance

1983
This chapter concerns linear models of the form $$ y = X\beta + e $$ with e ~ N(0, σ 2 Iwhere y and e are random vectors of length N, X is an N × p matrix of constants, s is a vector of p parameters and I is the unit matrix. These models differ from the regression models of the previous chapter in that X, called the design matrix, consists ...
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Nonparametric Analysis of Covariance by Matching

Biometrics, 1982
The basic problem under consideration is the comparison of treatments with respect to a response Y when a covariable X is taken into account. Various methods involving matching may be regarded as compromises between the standard analysis of covariance and the standard analysis of independent matched pairs.
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Adding additional covariates and the Analysis of Covariance

2010
Suppose that having fitted the regression model $$\vec{y} = X\beta + \epsilon, $$ (M0) we wish to introduce qadditional explanatory variables into our model. The augmented regression model, M A , say becomes $$\vec{y} = X\beta + Z\gamma + \epsilon.
N. H. Bingham, John M. Fry
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Analysis of Covariance with Interaction

Infection Control, 1981
Donald L. Kaiser, James E. Veney
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Covariance matrix estimation and classification with limited training data

IEEE Transactions on Pattern Analysis and Machine Intelligence, 1996
D A Landgrebe
exaly  

Brownian distance covariance

Annals of Applied Statistics, 2009
Gabor J Székely, Maria L Rizzo
exaly  

Structural analysis of covariance and correlation matrices

Psychometrika, 1978
Karl G Jöreskog, Jöreskog Karl G
exaly  

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